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Unsupervised texture segmentation using a nonlinear energy optimization method

JOURNAL OF ELECTRONIC IMAGING 2006年第3期15卷 033006.1-033006.8页

作者： Mahmoodi, Sasan Sharif, Bayan S. Univ Newcastle Sch Biol & Psychol Psychol Div Newcastle Upon Tyne NE2 4HH Tyne & Wear England Univ Newcastle Sch Elect Elect & Comp Engn Newcastle Upon Tyne NE1 7RU Tyne & Wear England

A nonlinear functional is considered for segmentation of images containing structural textures. A structural texture pattern in an image is characterized by a certain amplitude spectrum, and segmentation of different patterns is obtained by detecting different regions with different amplitude spectra. A gradient-descent-based algorithm is proposed by deriving equations minimizing the functional. This algorithm, implementing the solutions minimizing the functional, is based on the level set method. An effective method employed in this algorithm is shown to be robust in a noisy environment. Experimental results demonstrate that the proposed method outperforms segmentation obtained by using the simulated annealing algorithm based on Gaussian Markov random fields. (c) 2006 SPIE and IS&T.

关键词： image segmentation image processing algorithms and systems Multiplexers Expectation maximization algorithms Detection and tracking algorithms image filtering Reconstruction algorithms algorithms Smoothing Spatial frequencies

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image SEGMENTATION USING FUZZY RULES DERIVED FROM K-MEANS CLUSTERS

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JOURNAL OF ELECTRONIC IMAGING 1995年第2期4卷 199-206页

作者： CHI, Z YAN, H Univ. of Sydney (Australia)

image segmentation is one of the most important steps in computerized systems for analyzing geographic map images. We present a segmentation technique, based on fuzzy rules derived from the K-means clusters, that is aimed at achieving human-like performance, In this technique, the K-means clustering algorithm is first used to obtain mixed-class clusters of training examples, whose centers and variances are then used to determine membership functions, Based on the derived membership functions, fuzzy rules are learned from the K-means cluster centers. In the map image segmentation, we make use of three features, difference intensity, standard deviation, and a measure of the local contrast, to classify each pixel to the foreground which consists of character and line patterns, and to the background. A centroid defuzzification algorithm is adopted in the classification step. Experimental results on a database of 22 gray-scale map images show that the technique achieves good and reliable results, and is compared favorably with an adaptive thresholding method By using K-means clustering, we can build a segmentation system of fewer rules that achieves a segmentation quality similar to that of using the uniformly distributed triangular membership functions with the fuzzy rules learned from all the training examples.

关键词： image segmentation Fuzzy logic image processing algorithms and systems Digital imaging Databases image analysis Feature extraction Pattern recognition Computing systems Neural networks

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Integration of color, edge, shape, and texture features for automatic region-based image annotation and retrieval

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JOURNAL OF ELECTRONIC IMAGING 1998年第3期7卷 684-700页

作者： Saber, E Tekalp, AM Xerox Corp Print Cartridge Delivery Unit Webster NY 14580 USA Univ Rochester Dept Elect Engn Rochester NY 14627 USA Univ Rochester Ctr Elect Imaging Syst Rochester NY 14627 USA

We present algorithms for automatic image annotation and retrieval based on color, shape, texture, and any combination of two or more of these features. Pixel- or region (object)-based color. region-based shape;and block- or region-based texture features have been considered. Automatic region selection has been accomplished by integrating color and spatial edge features. Color, shape, and texture indexing may be knowledge based (using appropriate training sets) or by example. The multifeature integration algorithms are designed to: (i) offer the user a wide range of options and flexibilities in order to enhance the outcome of the search and retrieval operations, and (ii) provide a compromise between accuracy and computational complexity, and vice versa. We demonstrate the performance of the proposed algorithms on a variety of images. (C) 1998 SPIE and IS&T. [S1017-9909(98)02603-8].

关键词： image segmentation image classification image retrieval image processing algorithms and systems Feature extraction Shape analysis Databases Information fusion Imaging systems Visualization

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Accurate length measurement of multiple cotton fibers

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JOURNAL OF ELECTRONIC IMAGING 2008年第3期17卷 031110-031110-10页

作者： Wang, Huapeng Mao, Cui Sari-Sarraf, Hamed Hequet, Eric F. Texas Tech Univ Dept Elect & Comp Engn Lubbock TX 79409 USA Texas Tech Univ Int Text Ctr Lubbock TX 79409 USA

We present the design and realization of an imaging system intended for use as a reference method for the accurate measurement of cotton fiber length. The prototype system is composed of an off-the-shelf scanner that generates a grayscale image of multiple individualized fibers, followed by customized image processing algorithms that compute the length of each fiber in the image. Although the system requires some degree of separation between the individual fibers at scan time, it is shown to produce highly accurate length measurements that are invariant to fiber orientation, shape, interfiber intersections, and intrafiber crimps and crossovers. Hence, in its present state, the proposed system serves as an excellent reference method for assessing the efficacy of commercially available length measurement systems. (C) 2008 SPIE and IS&T. [DOI: 10.1117/1.2952846]

关键词： Adaptive control image acquisition Imaging systems Scanners image processing algorithms and systems

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Activity driven nonlinear diffusion for color image watershed segmentation

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JOURNAL OF ELECTRONIC IMAGING 1999年第3期8卷 270-278页

作者： De Smet, P Pires, RLVPM De Vleeschauwer, D Bruyland, I Univ Ghent Dept Telecommun & Informat Proc B-9000 Ghent Belgium

Nonlinear diffusion processes and watershed algorithms have been well studied for gray-scale image segmentation. In this paper we extend the use of these techniques to color or multichannel images. First, we formulate a general definition for a nonlinear diffusion process using the concept of an activity image that can be calculated for several image components. Then, we explain how the final activity image, obtained as a result of the nonlinear diffusion process, is fed through a watershed algorithm, yielding the segmentation of the image. The qualitative performance of the algorithm is illustrated with results for both gray-scale and color photographic images. Finally, we discuss the segmentation results obtained using a few well-known color spaces and demonstrate that a color principal component analysis gives the best results. (C) 1999 SPIE and IS&T. [S1017-9909(99)00503-6].

关键词： image segmentation Diffusion image processing image processing algorithms and systems RGB color model Color image processing image enhancement image compression Photography Principal component analysis

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image fusion and unsupervised joint segmentation using a HMM and MCMC algorithms -: art. no. 023014

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JOURNAL OF ELECTRONIC IMAGING 2005年第2期14卷 1-12页

作者： Féron, O Mohammad-Djafari, A Supelec UPS CNRS UMR8506LSS F-91192 Gif Sur Yvette France

In this paper we propose a Bayesian framework for unsupervised image fusion and joint segmentation, More specifically we consider the case where we have observed images of the same object through different imaging processes or through different spectral bands (multi- or hyperspectral images). The objective of this work is then to propose a coherent approach to combine these images and obtain a joint segmentation which can be considered as the fusion result of these observations. The proposed approach is based on a hidden Markov modeling of the images where the hidden variables represent the common classification or segmentation labels. These label variables are modeled by the Potts Markov random field. We propose two particular models for the pixels in each segment (iid. or Markovian) and develop appropriate Markov chain Monte Carlo algorithms for their implementations. Finally we present some simulation results to show the relative performances of these models and mention the potential applications of the proposed methods in medical imaging and survey and security imaging systems. (c) 2005 SPIE and IS&T.

关键词： image fusion image segmentation Data fusion Data modeling Medical imaging Magnetic resonance imaging image processing algorithms and systems Monte Carlo methods Reconstruction algorithms image classification

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Automatic segmentation of fiducial marks using attribute-based mathematical morphology

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JOURNAL OF ELECTRONIC IMAGING 2001年第2期10卷 560-566页

作者： Sun, C Wu, XL CSIRO N Ryde NSW 1670 Australia CSIRO Wembly WA 6014 Australia

This paper described a fast and automatic method for segmenting fiducial marks in an image taken with a metric camera. These marks could be at the four corners, four middle sides, or inside an image (reseau marks). The segmentation was realized by using attribute-based mathematical morphology techniques. The attributes that we used in the morphology processing step were the area, aspect ratio, and orientation of the best fitted ellipse of an object. The algorithm took about 0.25 s in the automatic segmentation stage. The positions of these automatically segmented fiducial marks were then refined to subpixel accuracy. Dozens of real images with different shapes of fiducial marks were tested and reliable results were obtained. Accuracy comparisons were made using our method and previously published methods. (C) 2001 SPIE and IS&T.

关键词： image segmentation image filtering Cameras image processing Databases image processing algorithms and systems Mathematical morphology Photography Calibration Digital filtering

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Bayesian image reconstruction from Fourier-domain samples using prior edge information

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JOURNAL OF ELECTRONIC IMAGING 2005年第4期14卷 043009.1-043009.1页

作者： Denney, TS Reeves, SJ Auburn Univ Auburn AL 36849 USA

We propose the Bayesian image reconstruction with prior edges ( BIRPE) algorithm for reconstructing an image from Fourier-domain samples with prior edge information from a higher resolution image. A major difference between BIRPE and previous methods is that all edges are detected automatically, and no segmentation of the prior image is required. Also, an edge found in the prior image does not need to be confirmed by the observations;smoothing is reduced across the edge if either the prior image or the observations suggest an edge. Simulations and results on magnetic resonance spectroscopic data are presented that demonstrate the effectiveness of the BIRPE method. (c) 2005 SPIE and IS&T.

关键词： Reconstruction algorithms image restoration Signal to noise ratio Magnetic resonance imaging image segmentation Algorithm development image processing algorithms and systems Tissues Edge detection Magnetism

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Markovian segmentation and parameter estimation on graphics hardware

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JOURNAL OF ELECTRONIC IMAGING 2006年第3期15卷 033005.1-033005.1页

作者： Jodoin, Pierre-Marc Mignotte, Max Univ Montreal Dept Informat & Rech Operat Montreal PQ H3C 3J7 Canada

In this paper, we show how Markovian strategies used to solve well-known segmentation problems such as motion estimation, motion detection, motion segmentation, stereovision, and color segmentation can be significantly accelerated when implemented on programmable graphics hardware. More precisely, we expose how the parallel abilities of a standard graphics processing unit usually devoted to image synthesis can be used to infer the labels of a segmentation map. The problems we address are stated in the sense of the maximum a posteriori with an energy-based or probabilistic formulation, depending on the application. In every case, the label field is inferred with an optimization algorithm such as iterated conditional mode (ICM) or simulated annealing. In the case of probabilistic segmentation, mixture parameters are estimated with the K-means and the iterative conditional estimation (ICE) procedure. For both the optimization and the parameter estimation algorithms, the graphics processor unit's (GPU's) fragment processor is used to update in parallel every labels of the segmentation map, while rendering passes and graphics textures are used to simulate optimization iterations. The hardware results obtained with a mid-end graphics card, show that these Markovian applications can be accelerated by a factor of 4 to 200 without requiring any advanced skills in hardware programming. (c) 2006 SPIE and IS&T.

关键词： image segmentation Visualization Motion estimation Motion detection Optimization (mathematics) C++ Motion models Computer programming Stochastic processes image processing algorithms and systems

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Segmentation-based lossless compression of burn wound images

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JOURNAL OF ELECTRONIC IMAGING 2001年第3期10卷 720-726页

作者： Serrano, C Pinero, BA Rangayyan, RM Roa, LM Univ Seville Escuela Super Ingenieros Aera Teoria Senal & Comunicac Seville 41092 Spain Univ Calgary Dept Elect & Comp Engn Calgary AB T2N 1N4 Canada Univ Seville Escuela Super Ingenieros Grp Ingn Biomed Seville 41092 Spain

Color images may be encoded by using a gray-scale image compression technique on each of the three color planes. Such an approach, however, does not take advantage of the correlation existing between the color planes. In this paper, a new segmentation-based lossless compression method is proposed for color images. The method exploits the correlation existing among the three color planes by treating each pixel as a vector of three components, performing region growing and difference operations using the vectors, and applying a color coordinate transformation. The method performed better than the Joint Photographic Experts Group (JPEG) standard by an average of 3.40 bits/pixel with a database including four natural color images of scenery, four images of burn wounds, and four fractal images, and it outperformed the Joint Bi-Level image experts Group (JBIG) standard by an average of 3.01 bits/pixel. When applied to a database of 20 burn wound images, the 24 bits/pixel images were efficiently compressed to 4.79 bits/pixel, then requiring 4.16 bits/pixel less than JPEG and 5.41 bits/pixel less than JBIG. (C) 2001 SPIE and IS&T.

关键词： image compression image segmentation RGB color model image quality standards Fractal analysis image processing algorithms and systems 3D image processing Photography Databases Digital photography

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